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Du côté de chez Proust: du végétal à l’esthétique
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In this paper, we take a look at algorithms involved in the computation of the Duquenne–Guigues basis of implications. The most widely used algorithm for constructing the basis is Ganter’s Next Closure, designed for generating closed sets of an arbitrary closure system. We show that, for the purpose of generating the basis, the algorithm can be optimized. We compare the performance of the original algorithm and its optimized version in a series of experiments using artificially generated and real-life datasets. An important computationally expensive subroutine of the algorithm generates the closure of an attribute set with respect to a set of implications. We compare the performance of three algorithms for this task on their own, as well as in conjunction with each of the two versions of Next Closure.
We present a context-based semantics for parameterized ceteris paribus preferences over attributes subsets. Such preferences are only required to hold when the alternatives being compared agree on a specified subset of attributes. We show that ceteris paribus preferences valid in a preference context correspond to implications of a special formal context derived from the original preference context. We prove that the problem of checking the semantic consequence relation for parameterized ceteris paribus preferences is coNP-complete. We then discuss the relation between parameterized and classical, i.e., non-parameterized, ceteris paribus preferences, which are only required to hold “all other things being equal”. We show that a non-parameterized preference is a special case of a parameterized preference, while any parameterized preference can be represented by an exponentially large set of non-parameterized preferences.
In this paper, we consider algorithms involved in the computation of the Duquenne–Guigues basis of implications. The most widely used algorithm for constructing the basis is Ganter’s Next Closure, designed for generating closed sets of an arbitrary closure system. We show that, for the purpose of generating the basis, the algorithm can be optimized. We compare the performance of the original algorithm and its optimized version in a series of experiments using artificially generated and real-life datasets. An important computationally expensive subroutine of the algorithm generates the closure of an attribute set with respect to a set of implications. We compare the performance of three algorithms for this task on their own, as well as in conjunction with each of the two algorithms for generating the basis. We also discuss other approaches to constructing the Duquenne–Guigues basis.
В статье рассматриваются особенности устной части международного экзамена по французскому языку DELF B2.Опираясь на опыт работы в качестве экзаменатора Нижегородской культурно-просветительской общественной организации "Альянс Франсез", автор рассматривает требования, предъявляемые к говорению, знакомит читателей с шкалой оценивания, проблематикой текстовых документов, анализирует трудности.